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@viktoriiagolovtseva shared a post, 7 months, 1 week ago

How to Link Issues in Jira Manually and Automatically

Connecting issues in Jira serves many purposes. For instance, it allows you to track dependencies between tasks, identify blockers, and visualize these blockers in a timeline view. As a result, you can better organize your team’s work, enhance planning, and improve collaboration.

In this blog post, I explain how to link issues in Jira using different methods. You can link issues automatically or manually from a Jira board or issue view. Additionally, we give you useful tips on how to make working with linked issues more convenient and efficient.

Screenshot 2025-10-15 at 11.56.06
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@shurup shared a post, 7 months, 1 week ago
@palark

New features introduced in Kubernetes 1.34

Kubernetes

Recently, the latest Kubernetes version, v1.34, was released with 13 new alpha features on board. They include: - KYAML, a new dialect of YAML for Kubernetes manifests, which is still compatible with all existing tooling; - asynchronous API calls to kube-apiserver during scheduling; - various enhanc..

kubernetes 1.34 release
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@laura_garcia shared a post, 7 months, 1 week ago
Software Developer, RELIANOID

🚀 Load Balancing and High Availability of Skype for Business with RELIANOID

Unified communication platforms like Skype for Business play a critical role in keeping teams connected through instant messaging, voice, and video — but maintaining high performance and availability is key. That’s where RELIANOID ADC comes in. 💪 In our latest article, we explain how to optimize Sky..

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@anjali shared a link, 7 months, 1 week ago
Customer Marketing Manager, Last9

Choosing the Right APM for Go: 11 Tools Worth Your Time

Explore 11 APM tools built for Go—from lightweight open-source options to enterprise-grade platforms that simplify debugging.

go
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@faun shared a link, 7 months, 1 week ago
FAUN.dev()

Development gets better with Age

A longtime AWS insider, Werner Vogels, breaks down the shift from slow-and-steady software growth to the generative AI rocket ride. Capabilities soared. Guardrails? Not so much. No docs, no handrails - just launch and learn. AWS didn’t chase the hype. It pulled a classic AWS move: doubled down on B2.. read more  

Development gets better with Age
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@faun shared a link, 7 months, 1 week ago
FAUN.dev()

Going down the rabbit hole of Postgres 18 features by Tudor Golubenco

PostgreSQL 18 just hit stable. Big swing! Async IO infrastructureis in. That means lower overhead, tighter storage control, and less CPU getting chewed up by I/O. Adddirect IO, and the database starts flexing beyond traditional bottlenecks. OAuth 2.0? Native now. No hacks needed. UUIDv7? Built-in su.. read more  

Going down the rabbit hole of Postgres 18 features by Tudor Golubenco
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@faun shared a link, 7 months, 1 week ago
FAUN.dev()

I'm Building a Browser for Reverse Engineers

A researcher rolled their ownChromium forkwith a customDevTools Protocol (CDP) domain- not for fun, but to surgically probe browser internals. It reaches into Canvas, WebGL, and other trickier APIs, dodging the usual sandbox and spoofing all the bot blockers they'd rather you leave alone. It injects.. read more  

I'm Building a Browser for Reverse Engineers
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@faun shared a link, 7 months, 1 week ago
FAUN.dev()

Advanced PostgreSQL Indexing: Multi-Key Queries and Performance Optimization

Advanced PostgreSQL tuning gets real results: composite indexes and CTEs can cut query latency hard when slicing huge datasets. AddLATERALjoins and indexed subqueries into the mix, and you’ve got a top-N query pattern that holds up—even when hammering long ID lists... read more  

Advanced PostgreSQL Indexing: Multi-Key Queries and Performance Optimization
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@faun shared a link, 7 months, 1 week ago
FAUN.dev()

Inside Husky’s query engine: Real-time access to 100 trillion events

SteamPipe just gutted its real-time storage engine and rebuilt it inRust. Expect faster performance and better scaling. Now runs oncolumnar storage, ships withvectorized queries, and rolls anobject store-backed WAL. Serious firepower for time series data. System shift:Another sign that high-throughp.. read more  

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@faun shared a link, 7 months, 1 week ago
FAUN.dev()

walrus: ingesting data at memory speeds

Walrusis a lock-free, single-nodeWrite Ahead Log in Rustthat rips through a million ops/sec and moves 1 GB/s of write bandwidth - on bare-metal, nothing fancy. It leans on mmap-backed sparse files, atomic counters, and zero-copy reads to get there. Each topic gets its own line of 10MB memory-mapped .. read more  

walrus: ingesting data at memory speeds
TruffleHog is a high-accuracy secret-detection tool designed to uncover exposed credentials such as API keys, tokens, private keys, and cloud secrets across large codebases. Originally created to scan Git commit history, it has evolved into a multi-source scanning engine capable of analyzing GitHub, GitLab, Bitbucket, Docker images, file systems, Terraform states, and cloud environments.

The scanner combines entropy detection, an extensive library of regular expression detectors, and live credential validation to minimize false positives. TruffleHog is widely used in security research, supply chain security, DevSecOps workflows, and bug bounty programs. Its speed, accuracy, and broad ecosystem coverage make it a core tool for identifying and preventing credential leakage in modern software development.